One additional related effort is the deep watershed transform for instance segmentation [1]}. This approach goes beyond the DCAN approach by providing direct positional awareness in the head of the network rather than only edge awareness as in the DCAN architecture. Models with the deep watershed transform architecture attempt to learn two things: unit vectors pointing to / against the boundary, and the distance of each pixel from the edge.
